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Field
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imaging. Develop, adapt, and evaluate modern reconstruction algorithms for accelerated and robust qMRI. Collaborate with a multidisciplinary team to translate methods to clinical research studies and
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning
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, collaborative work environment that can be deeply rewarding for the right individual. Further information is available at http://www.sci.utah.edu/ . Opportunities for Professional Development Through
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validate signal processing algorithms and stimulation strategies using electrophysiological and behavioral data. Develop GUIs, psychophysical test protocols, and objective outcome measures (e.g., ECAP, ABR
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. To support ORNL strategic research and development activities at the Manufacturing Demonstration Facility (MDF) (https://www.ornl.gov/facility/mdf/ ), we are accepting applications for Postdoctoral Research
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advantage through coherence-driven materials design and realizing scalable, modular quantum systems. These efforts integrate vertical co-design, from materials to algorithms, and cross-platform co-design
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. university groups within CMS. Our instrumentation expertise spans detector operations and upgrades (Level‑1 muon trigger, CSC muon system), tracking algorithm R&D, and future HL‑LHC trigger algorithm
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development of detectors sensitive to ultra-high dose rates. Developments of computation methods for small-field dosimetry, radiation detection systems used in photon, proton, and electron beam radiation
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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network modeling to address real-world policy challenges through algorithm development and technical analysis. Key Responsibilities Conduct original research in generative AI Train and supervise graduate